Motion artifacts removal for fNIRS data based on independent component analysis

Functional near-infrared spectroscopy (fNIRS) is a powerful tool in the functional brain imaging field. However, in practical applications, motion artifacts are often found in fNIRS data. In this study, we propose a new method based on independent component analysis to remove motion artifacts. The method uses the positive correlation between oxy-Hb and deoxy-Hb induced by motion artifacts. To demonstrate the feasibility of the method, we tested it on fNIRS data that contained motion artifacts collected from four participants. The results showed that: (a) the mean SNR of deoxy-Hb and oxy-Hb were improved 2.336 and 2.139 by our method, respectively; (b) the mean SNR of deoxy-Hb and oxy-Hb were improved 1.191 and 1.118 by the wavelet-based method, respectively. These results suggested that our method is better than the wavelet-based method.

[1]  F. Mosteller,et al.  Understanding robust and exploratory data analysis , 1985 .

[2]  David A Boas,et al.  Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging. , 2005, Journal of biomedical optics.

[3]  G. Dumont,et al.  Wavelet based motion artifact removal for Functional Near Infrared Spectroscopy , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[4]  Meltem Izzetoglu,et al.  Motion artifact cancellation in NIR spectroscopy using Wiener filtering , 2005, IEEE Transactions on Biomedical Engineering.

[5]  F. Jöbsis.  Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. , 1977, Science.

[6]  Quan Zhang,et al.  Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: How well and when does it work? , 2009, NeuroImage.

[7]  David A. Boas,et al.  A Systematic Comparison of Motion Artifact Correction Techniques for Functional Near-Infrared Spectroscopy , 2012, Front. Neurosci..

[8]  Tomoyuki Hiroyasu,et al.  Method for removing motion artifacts from fNIRS data using ICA and an acceleration sensor , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[9]  Tania S. Douglas,et al.  Motion Artifact Removal for Functional Near Infrared Spectroscopy: A Comparison of Methods , 2010, IEEE Transactions on Biomedical Engineering.

[10]  Clare E Elwell,et al.  Automatic detection of motion artifacts in infant functional optical topography studies. , 2010, Advances in experimental medicine and biology.

[11]  Frederick Mosteller,et al.  Understanding robust and exploratory data analysis , 1983 .

[12]  Xu Cui,et al.  Functional near infrared spectroscopy (NIRS) signal improvement based on negative correlation between oxygenated and deoxygenated hemoglobin dynamics , 2010, NeuroImage.